1. Field of the Invention
The present invention relates to an apparatus for converting an image signal which represents an image having a gradation, and more particularly, to an image processing apparatus for automatically establishing reference points (highlight and/or shadow points) in a gradation converter which is mounted therein.
2. Description of the Prior Art
As an image processing apparatus for generating a halftone dot image (reproduced image) from an original image, a color process scanner disclosed in U.S. Pat. No. 4,679,095 by the inventor of the present invention is known. The color process scanner disclosed in the '095 patent comprises a scanning reader 101, an image processor 102, a scanning recorder 103, a display device 104 and an information processor 105 as shown in FIG. 18.
The scanning reader 101 reads the image data of an original image (not shown) mounted on an input cylinder (or an original table). The original image consists of arrays of pixels and the image data are fed as electrical signals each expressing the density of each pixel of the pixel arrays.
The image processor 102 comprises a look-up table for setting up a gradation curve which represents conversion characteristics or a color computation circuit or the like for converting image data regarding the color components B, G and R into image data regarding the color components Y, M, C and K. In the image processor 102, the input image data read by the scanning reader 101 are processed at the look-up table or the color computation circuit or the like. Thus, the input image data are converted into output image data.
The scanning recorder 103 comprises a dot generator for converting the output image data received from the image processor 102 into a halftone dot signal in accordance with which a halftone dot image is recorded onto a photosensitive material (not shown) which is wound on an output cylinder (or which is fed on a plane).
The display device 104 comprises a CRT display (not shown in FIG. 18) as a display main unit. An image based on the image data processed by the image processor 102 is displayed on the CRT display.
The information processor 105 comprises a console, a CPU, a memory and the like. In accordance with the input image data read by the scanning reader 101, the information processor 105 calculates a gradation curve to be set up in the look-up table of the image processor 102. In addition, the information processor 105 is capable of amending the gradation curve and designating any desired region of the image which is displayed on the CRT display of the display device 104 by means of the console.
The information processor 105 sets up the gradation curve in the following manner.
First, the original image is prescanned to obtain the input image data. The input image data are processed by the image processor 102 in which standard set-up conditions have been set standard. The display device 104 displays an image A (See FIG. 9A) in accordance with the processed image data.
Next, an operator designates a subject region B (See FIG. 9A) of the image, A by operating the console of the information processor 105 while observing the image A.
Following this, based on the image data about the subject region B of the input image data read by prescanning, a density histogram such as that shown in FIG. 19 is obtained. The density histogram shows a relation between the density of the subject region B and the number of pixels which defines the density in the subject region B (i.e., appearance frequencies of pixels). In FIG. 19, indicated at reference character DM is a density rank value and indicated at reference character N is the number of the pixels (i.e., appearance frequencies of pixels).
Next, the pixel appearance frequencies in the density histogram are serially accumulated in increasing order of the density rank value to develop a cumulative density histogram as that shown in FIG. 20. In FIG. 20, a cumulative value of the appearance frequencies is shown as a relative frequency. Indicated at reference character DM in FIG. 20 is a density value and RN is a cumulative relative frequency of the pixels.
Cumulative relative frequencies RNH and RNS are then determined. The cumulative relative frequencies RNH and RNS are necessary to find an optimum highlight density DH and an optimum shadow density DS. The cumulative relative frequencies RNH and RNS are obtainable by experience, for example, from a number of sample originals which are prepared in advance. In most cases, the cumulative relative frequency RNH is around 1% and the cumulative relative frequency RNS is around 98%.
The cumulative relative frequencies RNH and RNS are thereafter applied to the cumulative density histogram of FIG. 20 to thereby find density rank values which correspond to the cumulative relative frequencies RNH and RNS. The density rank values are determined as the highlight density DH and the shadow density DS, respectively.
Output halftone area rates which correspond to the highlight density DH and the shadow density DS are then set in order to determine a highlight point HL and a shadow point SD each serving as a reference point of a gradation curve on a density conversion coordinate plane (FIG. 21).
Next, a gradation curve which passes through the highlight point HL and the shadow point SD is generated. The gradation curve may be a gradation curve with standard characteristics which is preliminarily selected in accordance with the original image, or may be developed by a known method, e.g., the method disclosed by the inventor of the present invention in U.S. Pat. No. 4,792,979. U.S. Pat. No. 4,792,979 discloses that an original image is prescanned to generate the density histogram in accordance with which a second gradation curve is developed. The second gradation curve is then combined with a first gradation curve with standard characteristics which has been preliminarily prepared to thereby generate a third gradation curve which will be determined as a gradation curve which passes through the highlight point HL and the shadow point SD.
Based on the gradation curve generated in this manner, the image data are gradation-converted. A resultant output image is displayed by the display device 104. The operator manipulates the information processor 105 while observing the image displayed by the display device 104. Thus, the gradation curve is adjusted if necessary.
The adjusted gradation curve is then set up in a look-up table which is stored in the image processor 102.
After setting up the gradation curve in the look-up table, the original image,is scanned by the scanning reader 101, thereby generating a reproduced image having a gradation which is converted in accordance with the gradation curve which is set up in the look-up table.
As hereinabove described, conventional gradation conversion demands an operator's manual work of designating the subject region B which is to be processed prior to setting up of the gradation curve, i.e., establishment of the reference density points. As with the case of the color process scanner described above, in particular, which is to be adaptive to various types of originals, mounting angles of an original image and etc., the subject region B cannot be easily determined in the same manner. Hence, manual designation of the subject region B by an operator is indispensable. This prevents unmanned operation of the above color process scanner, and remains as an obstacle to complete automatic operation of the color process scanner.